SciPy

Miscellaneous routines (scipy.misc)ΒΆ

Various utilities that don’t have another home.

Note that the Python Imaging Library (PIL) is not a dependency of SciPy and therefore the pilutil module is not available on systems that don’t have PIL installed.

ascent() Get an 8-bit grayscale bit-depth, 512 x 512 derived image for easy use in demos
bytescale
central_diff_weights(Np[, ndiv]) Return weights for an Np-point central derivative.
comb(N, k[, exact, repetition]) The number of combinations of N things taken k at a time.
derivative(func, x0[, dx, n, args, order]) Find the n-th derivative of a function at a point.
face([gray]) Get a 1024 x 768, color image of a raccoon face.
factorial(n[, exact]) The factorial function, n! = special.gamma(n+1).
factorial2(n[, exact]) Double factorial.
factorialk(n, k[, exact]) Multifactorial of n of order k, n(!!...!).
fromimage
imfilter
imread
imresize
imrotate
imsave
imshow
info([object, maxwidth, output, toplevel]) Get help information for a function, class, or module.
lena() Get classic image processing example image, Lena, at 8-bit grayscale bit-depth, 512 x 512 size.
logsumexp(a[, axis, b, keepdims, return_sign]) Compute the log of the sum of exponentials of input elements.
pade(an, m) Return Pade approximation to a polynomial as the ratio of two polynomials.
toimage
source(object[, output]) Print or write to a file the source code for a Numpy object.
who([vardict]) Print the Numpy arrays in the given dictionary.